The payments business is increasingly being driven by information. Strategies and execution through information insights can improve profitability, optimize revenue, and cut costs.. Big Data Analytics can introduce some major applications that result in reduction in payments fraud occurrences and in building a body of knowledge from customer data points in order to structure value-added services and create opportunities for cross selling. Here are some notable startups in the payments industry optimizing their solutions through big data analytics:
Back in November 2013, BillGuard made a prominent upgrade to its platform bringing in analytics capabilities. BillGuard utilizes Big Data Analytics in conjunction with reviews/insights from thousands of users to identify harmful or potentially fraudulent transactions in a user’s bank and credit card financial statements. It is basically an algorithmic, crowd-sourced approach to protecting and saving the user some money. The Spend Analytics feature of the platform offers personal finance management tools that will provide a wide range of analytics, enabling users to compare their current spending to earlier months. BillGuard also performs location based analytics to detect fraudulent transactions. When users opt-in for the service, BillGuard starts keeping track of locations where the user’s card is being used on a regular basis. It can use this data to match with the location of future transactions and alert users when a suspicious change occurs.
Wealthfront is one of the fastest growing automated investment services with over $1.2 billion in assets under management. The company leverages its horizontally scalable, modular, and pipelined data platform. Data is loaded from all origin sources: event ingestion, internal operational systems, external partner systems, SaaS APIs, and infrastructure service providers. Wealthfront uses Hadoop for offline batch processing via Cascading. A Cascading job rolls information up into daily metrics for each account, tracking things like account balance and daily rate of return. For each area of business, Weatherfront has built Dashboards that can be used to track things like new-feature adoption, the business at-large, and operational performance.
The company powers an online portfolio manager that looks at your existing investment portfolio and uses data analytics to recommend how to best invest your 401K savings. Jemstep’s technology compares data about every mutual fund/ETF with data about every other mutual fund/ETF to provide up-to-date market data. It combines this information with investor profiles, including financial goals, current situation, and investment preferences to make personalized recommendations for each investor.
By using big data analytics, SigFig provides a single view across multiple investment accounts and an in-depth analysis of those investments on a single dashboard. SigFig offers a portfolio tracker that provides real-time stock, bond, and mutual fund information, as well as detailed charts and analytics to dig down and review performance and investment allocation. Using the analytics driven dashboard, users can access asset allocation, geographic allocation, dividends, or risk to see which holdings are impacting the makeup of their investment portfolio.
Lending Club, one of the leading platforms for investing in and obtaining personal loans, uses Oracle ERP Cloud Service to help improve decision-making and workflow, and implement robust reporting. With its rapid growth as a data-intensive business, Lending Club is also implementing robust analytics and reporting techniques to help improve decision-making through the embedded business intelligence within Oracle ERP Cloud Service. Lending Club utilizes its data driven insights to reduce the cost of traditional banking and offer better rates and returns for its more than 76,000 borrowers and 90,000 investors. Lending Club has facilitated more than $5 billion in loans and has paid more than $300 million in interest to investors.
This social lending startup leverages social data analytics to make loans cost less. The company’s concept is to give consumers a way to receive lower interest rates on loans by having other family members and friends “vouch” for them. Vouch plots the user’s network and social ties in order to deduce credit worthiness within the loan application. The startup looks at a number of explicit and implicit factors to determine what interest rate it will offer a borrower. Factors considered are social data, including things like response rates for vouch requests, the overall size of someone’s network, how many “vouchers” took the extra step to also sponsor a loan, and much more.
Fundbox fills the void left by banks and credit companies, and fixes the small business economy using data science. Fundbox leverages newly available cloud services and deep data science to deliver financial services. By processing data based on tens of thousands of invoices daily, they offer small business owners the ability to fix their cash flow by advancing payments for unpaid invoices. Fundbox taps into numerous sources of data, including the user’s financial health, the demographics of their customers, and even the seasonal nature of some specific businesses. Leveraging cutting edge data science, behavioral analytics and finance theory, Fundbox automatically analyzes the user’s business and invoices not only from a financial perspective, but also from behavioral and psychological perspectives.